Nowadays, with the fast development of imaging and video technologies, video plays a key role as a mechanism of information exchange, transmission or storage. Video encoding has been deployed in many applications and equipment, ranging from digital cinema, mobile handsets, cable and satellite digital video transmissions, to machine vision and recognition systems, etc. With the proliferation of viewing platforms, file formats and streaming technologies competing in today's online media ecosystem, video encoding is becoming increasingly complicated and cumbersome. Optimal encoding and re-encoding of video content, such as, e.g., video compression and recompression, remains as a longstanding challenge in the field.
Given a particular video encoder, the goal of video encoding is often to create an encoded video which has maximal quality and best user experience, given a set of limited resources such as total bandwidth, computation power etc. Some of the currently available video encoders may focus on encoding at a certain bit-rate without considering the encoded video quality, whereas some others may target at achieving a given quality criterion while neglecting time and bit consumption of such encoding. It is widely acknowledged that a large part of the challenge consists in reliably and automatically determining the subjective quality of a candidate video clip, or of being able to obtain minimal bit-rate for a desired target quality, on a per clip or per title basis. It is challenging and complex to provide an optimal video encoding solution that is both efficient and cost-effective.